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Detection and prediction of Sitophilus oryzae infestations in triticale via visible and near-infrared spectral signatures
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Triticale is a hybrid of wheat and rye grown for use as animal feed. In Florida, due to its soft coat, triticale is highly vulnerable to Sitophilus oryzae L. (rice weevil) and there is interest in development of methods to detect early-instar larvae so that infestations can be targeted before they become economically damaging. The objective of this study was to develop prediction models of the infestation degree for triticale seed infested with rice weevils of different growth stages. Spectral signatures were tested as a method to detect rice weevils in triticale seed. Groups of seeds at 11 different levels (degrees) of infestation, 0–62%, were obtained by combining different ratios of infested and uninfested seeds. A spectrophotometer was used to measure reflectance between 400 and 2500 nm wavelength for seeds that had been infested at different levels with six different growth stages from egg to adult. The reflectance data were analyzed by several generalized linear regression and classification methods. Different degrees of infestation were particularly well correlated with reflectances in the 400–409 nm range and other wavelengths up to 967 nm, although later growth stages could be detected more accurately than early infestation. Stepwise variable selection produced the lowest mean square differences and yielded a high R² value (0.988) for the 4th instars, pupae and adults inside the seed. Models were developed to predict the level of infestation in triticale by rice weevils of different growth stages. Overall, this study showed a great potential of using reflectance spectral signatures for detection of the level of infestation of triticale seed by rice weevils of different growth stages

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Phytochemical Study of Cynara scolymus L. (Artichoke) (Asteraceae) Cultivated in Iraq, Detection and Identification of Phenolic Acid Compounds Cynarin and Chlorogenic Acid
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The leaves of globe artichoke, Cynara scolymus Family Asteraceae/ compositea have long – used in traditional medicine and now included in British and European Pharmacopeia, the British Harbal Pharmacopeia and complete German Commission E monographs.The plant originally comes from Mediterranean region and North Africa and cultivated around the world. The flowers are used worldwide for nutrition purposes and the leaves for medical purposes including hepatic affections. The plant wildly distributed in Iraq in the watery lines and boundary of the field.The plant contains many phytochemicals such as the bitter phenolic acids whose choleretic and hypocholestremic as these compounds are antioxidant. Other materials to h

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Publication Date
Wed Mar 28 2018
Journal Name
Indian Journal Of Natural Sciences
Detection of the Main Mycotoxins in Feed of Horses in Al-Zawra'a Park and Study their Effects on Hematological Feature
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Publication Date
Sat Sep 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction By Classical and Flow Zone Indictor (FZI) Methods for an Iraqi Gas Field
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The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

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Publication Date
Mon Oct 08 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
TOTAL ORGANIC CARBON (TOC) PREDICTION FROM RESISTIVITY AND POROSITY LOGS: A CASE STUDY FROM IRAQ
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     The open hole well log data (Resistivity, Sonic, and Gamma Ray) of well X in Euphrates subzone within the Mesopotamian basin are applied to detect the total organic carbon (TOC) of Zubair Formation in the south part of Iraq. The mathematical interpretation of the logs parameters helped in detecting the TOC and source rock productivity. As well, the quantitative interpretation of the logs data leads to assigning to the organic content and source rock intervals identification. The reactions of logs in relation to the increasing of TOC can be detected through logs parameters. By this way, the TOC can be predicted with an increase in gamma-ray, sonic, neutron, and resistivity, as well as a decrease in the density log

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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Spectral fluctuations in <sup>24</sup>Mg nucleus using the framework of the nuclear shell model
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Abstract<p>Random matrix theory is used to study the chaotic properties in nuclear energy spectrum of the <sup>24</sup>Mg nucleus. The excitation energies (which are the main object of this study) are obtained via performing shell model calculations using the OXBASH computer code together with an effective interaction of Wildenthal (W) in the isospin formalism. The <sup>24</sup>Mg nucleus is assumed to have an inert <sup>16</sup>O core with 8 nucleons (4protons and 4neutrons) move in the 1d<sub>5/2</sub>, 2s<sub>1/2</sub> and 1d<sub>3/2</sub> orbitals. The spectral fluctuations are studied by two statistical measures: the nearest neighb</p> ... Show More
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Publication Date
Sat Sep 03 2022
Journal Name
International Journal Of Health Sciences
Using Elisa and nested PCR for detection of the toxoplasmosis in milk and the influence of infection and some factors on milk composition in the Iraqi local and Shami goats
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This study concluded detection of Toxoplasma gondii in milk, immunologically by using Elisa and nested PCR)nPCR (based on B1 gene, also to investigate the effect of toxoplasmosis, parity, breed and flock on some milk composition in the Iraqi local and Shami goats in the middle of Iraq. A total of 80 milk samples of the lactating goats were collected. Results of this study showed the prevalence of Toxoplasmosis was 21.25% and 28.75% by Elisa and nPCR respectively without significant differences. The sensitivity of Elisa was a low (30.43%) whereas the specificity was a high (82.45%). The degree of agreement estimated by Kappa coefficient revealed a slight agreement (0.14) between two methods. The results indicated that goats infected

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Publication Date
Thu Sep 01 2022
Journal Name
Computers And Electrical Engineering
Automatic illness prediction system through speech
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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
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